Exploring the traffic sign recognition problem

dc.contributor.advisorHalawani, Alaa
dc.contributor.authorTalahmeh, Ala
dc.contributor.authorAmro, Asma
dc.contributor.authorMansour, Dua
dc.date.accessioned2022-03-28T06:05:57Z
dc.date.accessioned2022-05-22T08:16:38Z
dc.date.available2022-03-28T06:05:57Z
dc.date.available2022-05-22T08:16:38Z
dc.date.issued2009-06-01
dc.descriptionno of pages 62, 22889, تكنولوجيا المعلومات 6/2009 , in the store
dc.description.abstractIn this project a technique suggested as a solution for traffic sign recognition is presented. Scale-Invariant Feature Transform (SIFT) was examined to perform recognition (Detection and Classification). SIFT proved to be excellent in the detection and classification of traffic signs. Since SIFT is orientation invariant, orientation histogram used to make the feature orientation dependent. We used two databases of traffic signs images for testing the system, the result showed a success rate of (96.67%).en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/7663
dc.language.isoenen_US
dc.publisherجامعة بوليتكنك فلسطين - تكنولوجيا المعلوماتen_US
dc.subjectthe traffic signen_US
dc.titleExploring the traffic sign recognition problemen_US
dc.typeOtheren_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Exploring the Traffic Sign Recognition Problem .pdf
Size:
31.2 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description: